CO2 Monitoring Research Articles

Intelligent pointing increases the fraction of cloud-free CO2 and CH4 observations from space

For most CO2 and CH4 satellites, only a small percentage (∼10%) of observations yield successful retrievals, with the remaining ∼90% rejected, primarily due to the effects of clouds. Discarding this large fraction of data is an inefficient strategy worth reconsidering due to the costs involved in developing, launching and operating the satellites to make these observations. However, if real-time cloud data are available together with pointing capability, cloud data can guide the instrument pointing in an “intelligent pointing” strategy for cloud avoidance. In this work, multiple intelligent pointing simulations were conducted, demonstrating the significant advantages of this approach for satellites in a highly elliptical orbit (HEO), from which nearly the whole Earth disk can be observed. Multiple factors are shown to contribute to intelligent pointing efficiency such as the size and shape (or aspect ratio) of the field of view (FOV). For the current baseline orbit and Imaging Fourier Transform Spectrometer (IFTS) observing characteristics for the proposed Arctic Observing Mission (AOM), the monthly fraction of cloud-free observations is roughly a factor of 2 (ranging from ∼1.5–2.5) more than obtained with standard pointing (in which cloud information is not used). A similar efficiency is expected in a geostationary orbit (GEO) with an IFTS, however, for a dispersive instrument in HEO or GEO, the gain is more modest. This result is primarily attributed to the ∼1:1 aspect ratio of the IFTS FOV, since it is more efficient for cloud avoidance and scanning irregularly-shaped land masses than the long and narrow slit projection of a typical dispersive spectrometer. These results have implications for the design of future CO2 or CH4 monitoring satellites and constellation architectures, as well as other fields of satellite earth observation in which clouds significantly impact observations.

Improving CO2 sensing and p-n conductivity transition under UV light by chemo-resistive sensor based on ZnO nanoparticles

Chemo-resistive gas sensors for CO2 detection were fabricated using ZnO nanoparticles synthesized by the hydrothermal method. The CO2 sensors were activated by thermal and/or UV light exposure. While the resistance changes of sensors exposed to CO2 at high temperatures (150–300 °C) exhibited noise, those activated by UV light remained stable, indicating that UV light can improve CO2 sensing. Good response, short response time (<10 s), stability, a linear calibration curve, and high sensitivity were obtained under UV light. Therefore, the UV-activated sensor could be applied in practical environments for CO2 monitoring. Furthermore, the measurements for CO2 also showed that the p-n transition was observed with changes in temperature. The CO2 sensor acted as p-type at RT, while it acted as n-type at 80 °C. The p-type conductivity of ZnO at RT, which can be attributed to Zn vacancies acting as acceptors, was confirmed through PL and EDX spectra, as well as Hall Effect measurements. It should be noted that the p-n transition in sensors based on undoped materials under UV irradiation at low temperatures (<100 °C) has been less reported. The n-p transition could offer intriguing opportunities to customize the electronic properties of the nanostructured devices.

P084 Characteristics of sleep hypoventilation during polysomnography in a large Australian clinical sleep laboratory cohort.

Abstract BACKGROUND Sleep hypoventilation complicates a range of neurological and respiratory conditions. However, robust definitions are based mainly on expert consensus, and clinically significant thresholds remain unclear. This study thus aims to provide a descriptive analysis of capnography results in a large clinical cohort of patients referred for overnight polysomnography (PSG). METHODS Retrospective clinical audit of overnight in-lab PSGs, between Jan 2015 and June 2023, at a tertiary hospital housing the State-wide referral centre for chronic domiciliary ventilation. Diagnostic PSGs with transcutaneous CO2 (PTcCO2) monitoring and without supplemental oxygen were included. The following data will be extracted from each PSG: Patient demographics: -Primary and secondary clinical diagnoses -PTcCO2 values (e.g. Mean, Minimum and Maximum PTcCO2 in Wake, Sleep, NREM and REM) -Sleep fragmentation measures -Sleep macro-architecture measures -AHI -SpO2 values Data analysis will be performed with IBM SPSS Statistics software, version 26 (Armonk, NY: IBM Corp) PROGRESS TO DATE 525 PSGs meeting initial criteria have been identified. Currently processing PSG data files to extract parameters and complete exploratory data cleaning and analysis. INTENDED OUTCOME AND IMPACT We aim to explore and clarify: -Differences in patterns of hypoventilation between different diagnostic groups. -Relationships between awake hypoventilation, sleep hypoventilation and REM-isolated hypoventilation. -Effects of applying differing criteria for hypoventilation available in the literature. -Relationships between measures of sleep fragmentation, AHI, SpO2 and hypoventilation parameters. The results of this study will also support and inform future research into associations between severity, duration and patterns of hypoventilation and clinically significant outcomes including morbidity and mortality.

CO2 monitoring associated with the quality of soybean grains stored in different moisture contentes

The objective of this study was to quantify the levels of CO2 produced by soybeans stored at room temperature in a prototype silo, with initial moisture contents of 12, 14, and 16% (w.b.), as well as to evaluate the quality of the product over storage. Analyses of the moisture content, ash, proteins, lipids, color, germination, and electrical conductivity were performed. In the atmosphere in the silos, the amount of CO2, relative humidity, and temperature were monitored every hour using a CO2 meter data logger. Grain quality evaluations took place at four storage times (0, 30, 60, and 90 days). Analyses were performed in triplicate, and data were analyzed using analysis of variance and regression, adopting the 5% level of significance. The moisture contents, protein, lipids, germination, and color were reduced over time, resulting in a loss of grain quality. Soybeans initially stored with 16% (w.b.) of initial moisture content showed greater losses associated with the rise in the levels of CO2. The rise in CO2 emission in the internal atmosphere of the silo signals the beginning of grain deterioration and can be used as a decision-making tool, aiming at preventing and reducing losses in product quality over storage.

An ultra-small integrated CO2 infrared gas sensor for wearable end-tidal CO2 monitoring

Human physiological metabolic status can be obtained by monitoring exhaled CO2 concentration, but current CO2 sensors have disadvantages such as large size, high power consumption, and slow response time, which limit their application in wearable devices and portable instruments. In this article, we report a small size, good performance, and large range CO2 infrared gas sensor that integrates a high emissivity MEMS emitter chip, a high detectivity thermopile chip, and a high coupling efficiency optical chamber to achieve high efficiency optical-thermal-electrical conversion. Compared with typical commercial sensors, the size of the sensor can be reduced by approximately 80% to only 10mm×10mm×6.5mm, with the advantages of low power consumption and fast response speed. Further, a monitoring system for end-tidal CO2 concentration installed on a mask was developed using this sensor, and good results were achieved.

Multi-Scale Seismic Measurements for Site Characterization and CO2 Monitoring in an Enhanced Oil Recovery/Carbon Capture, Utilization, and Sequestration Project, Farnsworth Field, Texas

To address the challenges of climate change, significantly more geologic carbon sequestration projects are beginning. The characterization of the subsurface and the migration of the plume of supercritical carbon dioxide are two elements of carbon sequestration that can be addressed through the use of the available seismic methods in the oil and gas industry. In an enhanced oil recovery site in Farnsworth, TX, we employed three separate seismic techniques. The three-dimensional (3D) surface seismic survey required significant planning, design, and processing, but produces both a better understanding of the subsurface structure and a three-dimensional velocity model, which is essential for the second technique, a timelapse vertical seismic profile, and the third technique, cross-well seismic tomography. The timelapse 3D Vertical Seismic Profile (3D VSP) revealed both significant changes in the reservoir between the second and third surveys and geo-bodies that may represent the extent of the underground carbon dioxide. The asymmetry of the primary geo-body may indicate the preferential migration of the carbon dioxide. The third technique, cross-well seismic tomography, suggested a strong correlation between the well logs and the tomographic velocities, but did not observe changes in the injection interval.

The CCS greensand project: CO2 pilot injection and monitoring

The CCS greensand project: CO2 pilot injection and monitoring

Efficient and tunable broadband mid-infrared luminescence through energy transfer in CsPb1-x(Er/Yb/Ho)xBr3 perovskite fluoride glasses for CO2 monitoring in H2 energy

Inorganic CsPbBr3 perovskites have garnered significant attention for their excellent optoelectronic properties, particularly in the visible region. However, their great potential for mid-infrared applications has rarely been reported. In this study, we successfully synthesized CsPb1-x(Er/Yb/Ho)xBr3-ZBLAN perovskite fluoride glasses, which exhibit efficient and tunable broadband mid-infrared luminescence. We utilized this perovskite material to fabricate a detection device for measuring carbon dioxide impurity concentrations in hydrogen energy systems. By substituting the Pb2+ ions with rare earth ions Er3+/Yb3+/Ho3+, we achieved continuous tunability within the wavelength range of 2.6–3 μm. Absorption and emission cross sections (σabs and σem) of 0. 25CsPb1-x(Er/Yb/Ho)xBr3-ZBLAN are 3.14×10−20 cm2 and 3.45×10−20 cm2. These findings highlight the potential of CsPb1-x(Er/Yb/Ho)xBr3 perovskite fluoride glasses for future applications in broadly tunable mid-infrared light emitting and laser technologies. Overall, our results demonstrate the broad utility of CsPb1-x(Er/Yb/Ho)xBr3 perovskite fluoride glass for tunable mid-infrared luminescence and laser applications.

Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

Interventional Heartworm Extraction in Two Dogs: The Clinical Application of Impedance Cardiography.

This study aimed to assess the efficacy of using impedance cardiography (ICG) as a non-invasive approach for monitoring CO during interventional HW extraction. Two cases of HW infections were treated via surgical extraction. The CO and mean arterial pressure (MAP) were monitored using the ICG technique during the anesthesia stabilization, extraction process, and post-extraction phases. In Case 1, the CO increased by 115% post-procedure, and in Case 2, the CO increased by 116%. In contrast, the MAP varied between the two cases. The ICG method provided real-time CO data without major disruptions during the extraction surgery. The ICG technique for CO monitoring during interventional HW extractions is effective.

"Titrating Tobacco Treatment Medications Using Total Nicotine Equivalents and Expired Breath Carbon Monoxide: A Path to Increasing Quit Rates and Medical Revenues"

"Titrating Tobacco Treatment Medications Using Total Nicotine Equivalents and Expired Breath Carbon Monoxide: A Path to Increasing Quit Rates and Medical Revenues"

Enhanced expiratory rebreathing space for high loop gain sleep apnea treatment

The pathophysiology of sleep apnea goes beyond anatomic predisposition to airway collapse and includes additional factors such as arousal threshold and loop gain. High loop gain is a prominent feature in central and complex sleep apnea (with a mixture of obstructive and central features) where relative hypocapnia can lead to respiratory instability and periodic breathing. Existing therapies, including continuous positive airway pressure (CPAP) and adaptive servo-ventilators, often inadequately treat sleep apnea with high loop gain features. Enhanced expiratory rebreathing space (EERS) targets prevention of the hypocapnia that triggers central events in sleep by increasing dead space in amounts less than typical tidal volumes. This is accomplished by covering traditional exhalation ports on positive airway pressure masks and adding small additional tubing with distal exhalation and safety valves. This technique reduces carbon dioxide (CO2) blow-off during arousals and the associated large recovery breaths, typically producing a maximal increase in resting CO2 by 1–2 mmHg, thus increasing the CO2 reserve and making it less likely to encounter the hypocapnic apneic threshold. Typically, the amount of EERS is titrated in response to central events and periodic breathing rather than aiming for a goal CO2 level. Ideally CO2 monitoring is used during titration of EERS and the technique is avoided in the setting of baseline hypercapnia. This method has been used in clinical practice at our sleep center for over 15 years, and retrospective data suggests an excellent safety profile and high rates of successful therapy including in patients who have previously failed CPAP therapy. Limitations include decreased effectiveness in the setting of leak and decreased tolerance of the bulkier circuit. EERS represents a simple, affordable modification of existing positive airway pressure modalities for treatment of central and complex sleep apnea. Areas of future study include randomized controlled trials of the technique and study of use of EERS in combination with adaptive ventilation, and pharmacologic adjuncts targeting high loop gain physiology.

Polyaniline/Ti3C2Tx functionalized mask sensors for monitoring of CO2 and human respiration rate

Flexible and wearable gas-sensing devices have become increasingly crucial for monitoring air quality and human health. Disposable masks, mainly composed of polypropylene (PP) fibers, can serve as a potential flexible substrate for sensing devices yet have been largely overlooked during the COVID-19 pandemic. In the present work, flexible Ti3C2Tx/PANI-PP composite gas sensors were fabricated by spray-coating delaminated Ti3C2Tx MXene and in-situ polymerization of aniline on a disposable mask substrate. The resulting hybrid gas sensor displayed a wide detection range (25–1500 ppm), reliable reproducibility, long-term stability, and excellent flexibility and selectivity, a remarkable response (15.2%) towards 500 ppm CO2 gas, which is 6.5 times higher than pristine Ti3C2Tx and 2.4 times higher than pristine PANI. The enhanced sensing performance of the composite sensor is mainly attributed to the synergistic effects of the heterojunctions between Ti3C2Tx and PANI, the improved conductivity, and the enlarged specific surface area. We further investigated the influence of various parameters, including humidity, temperature, bending angles, and folding times on the sensing performance of the composite gas sensor. Finally, a wearable wireless Bluetooth sensing device was fabricated for human exhaled breath monitoring at room temperature, demonstrating the potential application of this Ti3C2Tx/PANI-PP composite sensor for respiratory disease diagnosis.

Long-Term Outcomes of a Comprehensive Mobile Smoking Cessation Program With Nicotine Replacement Therapy in Adult Smokers: Pilot Randomized Controlled Trial.

Increased smartphone ownership has led to the development of mobile smoking cessation programs. Although the related body of evidence, gathered through the conduct of randomized controlled trials (RCTs), has grown in quality and rigor, there is a need for longer-term data to assess associated smoking cessation durability. The primary aim was to compare smoking cessation outcomes at 52 weeks in adult smokers randomized to a mobile smoking cessation program, Pivot (intervention), versus QuitGuide (control). The secondary aims included comparison of other smoking-related behaviors, outcomes and participant feedback, and exploratory analyses of baseline factors associated with smoking cessation. In this remote pilot RCT, cigarette smokers in the United States were recruited on the web. Participants were offered 12 weeks of free nicotine replacement therapy (NRT). Data were self-reported via a web-based questionnaire with videoconference biovalidation in participants who reported 7-day point-prevalence abstinence (PPA). Outcomes focused on cessation rates with additional assessment of quit attempts, cigarettes per day (CPD), self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire, NRT use, and participant feedback. Cessation outcomes included self-reported 7- and 30-day PPA, abstinence from all tobacco products, and continuous abstinence. PPA and continuous abstinence were biovalidated using witnessed breath carbon monoxide samples. Exploratory post hoc regression analyses were performed to identify baseline variables associated with smoking cessation. Participants comprised 188 smokers (n=94, 50% in the Pivot group and n=94, 50% in the QuitGuide group; mean age 46.4, SD 9.2 years; n=104, 55.3% women; n=128, 68.1% White individuals; mean CPD 17.6, SD 9.0). Several cessation rates were higher in the Pivot group (intention to treat): self-reported continuous abstinence was 20% (19/94) versus 9% (8/94; P=.03) for QuitGuide, biochemically confirmed abstinence was 31% (29/94) versus 18% (17/94; P=.04) for QuitGuide, and biochemically confirmed continuous abstinence was 19% (18/94) versus 9% (8/94; P=.046) for QuitGuide. More Pivot participants (93/94, 99% vs 80/94, 85% in the QuitGuide group; P<.001) placed NRT orders (mean 3.3, SD 2.0 vs 1.8, SD 1.6 for QuitGuide; P<.001). Pivot participants had increased self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire (mean point increase 3.2, SD 7.8, P<.001 vs 1.0, SD 8.5, P=.26 for QuitGuide). QuitGuide participants made more mean quit attempts (7.0, SD 6.3 for Pivot vs 9.5, SD 7.5 for QuitGuide; P=.01). Among those who did not achieve abstinence, QuitGuide participants reported greater CPD reduction (mean -34.6%, SD 35.5% for Pivot vs -46.1%, SD 32.3% for QuitGuide; P=.04). Among those who reported abstinence, 90% (35/39) of Pivot participants and 90% (26/29) of QuitGuide participants indicated that their cessation program helped them quit. This pilot RCT supports the long-term effectiveness of the Pivot mobile smoking cessation program, with abstinence rates durable to 52 weeks. ClinicalTrials.gov NCT04955639; https://clinicaltrials.gov/ct2/show/NCT04955639.

Inter-comparison and evaluation of global satellite XCO2 products

ABSTRACT Carbon dioxide (CO2) is one of the main greenhouse gases and has become a major concern as its concentration has been growing in recent years. Satellite remote sensing is an efficient way to monitor CO2 in the atmosphere, and several satellites are already used for CO2 monitoring. It is imperative to investigate the spatial coverage and spatio-temporal trends of satellite products, as well as identify the satellites with higher levels of accuracy. Additionally, examining the disparities between the older and new generations of satellites would be meaningful. Therefore, this paper provides a comprehensive evaluation and inter-comparison for the commonly used satellite column-averaged dry-air mole fraction of CO2 (XCO2) products. Specifically, the temporal trends and monthly coverage of the Greenhouse Gases Observing SATellite (GOSAT), Greenhouse Gases Observing SATellite-2 (GOSAT-2), Orbiting Carbon Observatory-2 (OCO-2), Orbiting Carbon Observatory-3 (OCO-3), and SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) are investigated. The accuracy of these satellite products is evaluated and analyzed based on Total Carbon Column Observing Network (TCCON) data. The results indicate that the XCO2 of all the satellite products show a year-by-year increase, with seasonal periodicity. In terms of overall accuracy, the OCO series satellites exhibit a slightly higher level of accuracy compared to the GOSAT series. The products of the new generation of satellites are less stable than those of the older generation, probably due to the impacts of the inversion algorithm and platforms.

Structural improvement of Sm–Mn oxides for enhanced CO sensing performance

Restricted by an insufficient understanding of the compositional and structural characteristics of the sensing materials that affect the sensing performances, the YSZ-based CO gas sensor remains in a dilemma in terms of further promoting sensitivity, selectivity and long-term stability. In this work, two bimetallic oxides with different crystal structures, perovskite SmMnO3 and mullite SmMn2O5, were prepared and adopted to elucidate the roles of the Mn3+, Mn4+ and surface oxygen vacancies. Compared with SmMnO3, the coexisting coordination modes of Mn3+ and Mn4+ in SmMn2O5 is conducive to generating oxygen vacancies. Furthermore, a SmMn2O5-based sensor with more oxygen vacancies demonstrates a relatively faster response/recovery speed and enhanced sensitivity of 2.05 times that of SmMnO3 under the same operation conditions. Such work may broaden insight into the development of efficient sensing materials that introduce oxygen vacancies through the construction of phase structures without complicated operations. Overall, the sensor attached to SmMn2O5 exhibits a low detection limit (5 ppm), a feasible response/recovery speed (24 s/28 s toward 40 ppm CO operating at 450 °C), satisfactory CO selectivity and long-term stability, highlighting its potential for CO monitoring in harsh environments.

Three‐axis borehole gravity monitoring for CO2 storage using machine learning coupled to fluid flow simulator

AbstractThe field of geophysics faces the daunting task of monitoring complex reservoir dynamics and imaging carbon dioxide storage up to several decades into the future. This presents numerous challenges, including sensitivity to parameter changes, resolution of obtained results and the cost of long‐term deployment. To effectively store CO2 subsurface, it is necessary to monitor and account for the injected CO2. The gravity method provides several advantages for CO2 monitoring, as changes in fluid saturation correspond directly and uniquely to observed density changes. Three‐axis borehole gravity has demonstrated significant promise as a next‐generation tool for reliably monitoring reservoir dynamics across a range of depths and sizes. However, the gravity inverse problem is highly ill‐posed, necessitating regularization that incorporates prior knowledge. To address this issue, we propose using a feed‐forward neural network, a machine learning method, to invert time‐lapse three‐axis borehole gravity data and monitor CO2 movement within a reservoir. By training the neural network on models that analyse changes in density and corresponding gravity responses resulting from perturbations made to the reservoir model, we can create scenarios that train the algorithm to identify unexpected CO2 migration in addition to the normal movement of CO2. Our method is demonstrated using reservoir models for the Johansen formation in offshore Norway. We convert reservoir saturation models into density changes and generate their corresponding three‐axis gravity data in a set of boreholes. Our results show that the developed machine learning inversion algorithm has high reliability and resolution for imaging density change associated with CO2 plumes, as demonstrated in the Johansen reservoir models utilized by the simulator. We also investigate machine learning inversion using regularization parameters and show that it is robust, with a strong tolerance for higher levels of noise. Our study demonstrates that the developed machine learning algorithm is a powerful tool for inverting three‐axis borehole gravity data and monitoring the migration and long‐term storage of injected CO2.

A novel multifunctional fluorescent capillary-based sensor for simultaneous monitoring of pH, O2 and CO2

A fluorescent capillary sensor for detecting the bioanalytically and biologically relevant analytes pH, O2, and CO2 has been designed. The sensor is based on single capillary tube with 2 mm inner diameter, which is simultaneous doped with emissive O2-sensitive indicator Ru(dpp)3(PF6)2 (RuDP), pH-sensitive and CO2-sensitive indicator 8-hydroxypyrene-1, 3,6-trisulfonic acid trisodium salt (HPTS). The multifunctional sensor can be excited at the same wavelength and realize multi-parameter optical monitoring at the different sensing position. Studies in phosphate-buffered solutions display the excellent feasibility of the capillary sensor for fluorescence detection of pH, O2, and CO2. Overall, the multifunctional capillary sensor exhibits great potential in real-time blood gas analysis, and clinical application of multi-parameter biological detection.

Transcutaneous CO2 Monitoring in Extremely Low Birth Weight Premature Infants.

Extremely low birth weight (ELBW) premature infants are particularly susceptible to hypocarbia and hypercarbia, which are associated with brain and lung morbidities. Transcutaneous CO2 (TcCO2) monitoring allows for continuous non-invasive CO2 monitoring during invasive and non-invasive ventilation and is becoming more popular in the NICU. We aimed to evaluate the correlation and agreement between CO2 levels measured by a TcCO2 monitor and blood gas CO2 (bgCO2) among ELBW infants. This was a prospective observational multicenter study. All infants < 1000 g admitted to the participating NICUs during the study period were monitored by a TcCO2 monitor, if available. For each bgCO2 measured, a simultaneous TcCO2 measurement was documented. In total, 1828 pairs of TcCO2-bgCO2 values of 94 infants were collected, with a median (IQR) gestational age of 26.4 (26.0, 28.3) weeks and birth weight of 800 (702, 900) g. A moderate correlation (Pearson: r = 0.64) and good agreement (bias (95% limits of agreement)):(2.9 [-11.8, 17.6] mmHg) were found between the TcCO2 and bgCO2 values in the 25-70 mmHg TcCO2 range. The correlation between the TcCO2 and bgCO2 trends was moderate. CO2 measurements by TcCO2 are in good agreement (bias < 5 mmHg) with bgCO2 among premature infants < 1000 g during the first week of life, regardless of day of life, ventilation mode (invasive/non-invasive), and sampling method (arterial/capillary/venous). However, wide limits of agreement and moderate correlation dictate the use of TcCO2 as a complementary tool to blood gas sampling, to assess CO2 levels and trends in individual patients.

Whole person care: Outcomes from a 5-year care model integrating primary care into a behavioral health clinic.

Integrated mental and physical health care has the potential to improve health outcomes. A behavioral health organization established a reverse integration program site using a co-located model to provide primary care services to patients receiving behavioral health services. We ask whether this model of co-located care was effective in improving a range of physical health outcomes for clients. This program was funded with a grant from the Substance Abuse and Mental Health Services Administration Primary and Behavioral Health Care Integration. Patients received services in a community mental health setting that embedded primary care services. The population included adult patients with mental illness, substance use disorder (SUD), or co-occurring medical diagnoses in an urban setting. Just under half of the patients identified as non-White, and over one quarter identified as Hispanic. These characteristics demonstrate a medically complex and underserved population. This description and exploratory analysis utilized National Outcome Measures data and clinical health measures from electronic health records. We stratified data by SUD and mental illness diagnoses. We measured changes in health outcomes for this complex population of 532 patients from 2015 to 2019. From enrollment to last visit, patient outcomes improved for blood pressure and cholesterol. Conversely, waist circumference and breath carbon monoxide levels significantly worsened. This reverse integration co-location program demonstrates that positive health outcomes can be achieved through evidence-based care, adaptable clinic arrangements, and robust community connections and support. More work is needed to generate positive health outcomes in medically complex patients. (PsycInfo Database Record (c) 2023 APA, all rights reserved).